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EUROPEAN IDENTITY MATTERS

An empirical analysis of the impact of European Identity on the

opinion towards a possible EU accession of Turkey

Lukas Röber – s0214118 Campuslaan 37-214 7522NG Enschede +31 (0) 647237006

l.h.rober@student.utwente.nl Supervisor: Henk van der Kolk

2nd supervisor: Andreas Warntjen

Word count: 9,055

July 2011

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Abstract In this paper, relating attitudes towards Europe and attitudes towards the accession of Turkey are

contrasted and tested using a large survey among European citizens. Specifically two theories regarding

identity-related factors that might influence the opinion towards a possible accession of Turkey to the

EU are tested to determine the effects of European identity. On the one hand the widespread theory,

that identifying with Europe implies being more open to new members to spread the values and norms

of Europe. On the other hand stands the application of the Social Identity Theory, suggesting that

identification with Europe negatively influences the opinion towards Turkish EU-membership. A

regression analysis using data from the Eurobarometer 69.2 from 2008 is used to come about this task.

The main finding of this paper is that the data supports the former theory, showing that European

identity feeling has a positive impact on the support of Turkish membership. This means that people

identifying stronger with Europe are more inclined to have a positive attitude towards Turkey becoming

a member of the European Union.

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Table of Contents 1. Introduction and Research Question ................................................................................................. 4

2. Theory ............................................................................................................................................... 6

2.1. ‘Hard Factor’ Explanations ............................................................................................................ 6

2.2. ‘Soft Factor’ Explanations ............................................................................................................. 7

2.3. Hypotheses .................................................................................................................................. 10

3. Methodology ................................................................................................................................... 11

3.1. Research Design .......................................................................................................................... 11

3.2. Operationalization ...................................................................................................................... 13

4. Analysis ........................................................................................................................................... 17

5. Discussion and Conclusion .............................................................................................................. 24

Appendix ................................................................................................................................................. 28

Bibliography ............................................................................................................................................ 33

List of Figures 1 Eurobarometer 69.2 – Answers to question A45…………………………………………………………………………4

2 Scatterplot of the relationship between European Identity and Support for Turkey…………………17

List of Tables

1 Overview of all variables, including operationalization and descriptive statistics………………………29

2 Model Summary with dependent variable ‘Support for Turkey’ ……………………………………………….18

3 Coefficients with dependent variable ‘Support for Turkey’ – 1………………………………………………….19

4 Coefficients with dependent variable ‘Support for Turkey’ - 2…………………………………………………..20

5 Countries’ b-values with Italy as baseline………………………………………………………………………………….24

6 Coefficients with dependent variable ‘Support for Turkey’ – Complete…………………………………….31

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Figure 1: Eurobarometer 69.2 – Answers to question A45

1. Introduction

As the European Union has ever more grown since its establishment and is prone to keep on integrating

new members, public opinion plays in light of an overall democratic deficit discussion an important role

within the process of a wider integration. Especially the case of Turkey has always been highly debated

within the European Union (EU). As unique as the debate itself, is the development of EU-Turkey

relations. Since the establishment of the Turkish Republic in 1923, the Turkish state has been devoting

considerable efforts to belong entirely to Europe. However it was not until 2005 that the EU officially

started membership negotiations with Turkey (Hurd, 2006, p. 404). This step initiated a great discussion,

which had already seethed for decades, on whether Turkey belongs to Europe and whether it should

join the Union or not. Next to many political hurdles, as for example human rights and democratic

structures in Turkey, public concern is a key issue. Despite a high number of opposing EU citizens, the

integration process of Turkey has never come to a full halt. Recent Eurobarometers show that the public

is still broadly opposed to Turkey’s membership. Eurobarometer 69.2 from 2008 for example shows that

about half of the population takes a negative stance in the matter (Figure 1).

This leads to problems regarding the legitimacy of the European Union’s action to take on board new

members such as Turkey. Since the discussion of a democratic deficit within the European Union is

highly present in the last years (cf. for example Follesdal & Hix, 2006; Crombez, 2003), a lack of public

support for an issue as highly contested as Turkey’s membership could have critical consequences. An

inclusion of Turkey in the EU without public consent could throw the Union into a deep crisis of

legitimacy and a further loss in public trust. This is what makes public opinion so important. Hence by

determining the aspects shaping public opinion, this paper contributes to understanding the factors

influencing the public opposition in the EU towards the accession of Turkey.

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Naturally, with such large discontent with Turkey’s accession comes a high number of studies dealing

with this phenomenon. In recent years numerous studies came to the conclusion that identity related

factors play a, at least, catalytic role within public opinion formation (cf. for example Karp & Bowler,

2006; McLaren, 2007; Curley, 2009; Dixon, 2010). However findings and opinions diverge in the question

on what kind of influence the people’s identity and especially European identity has in this regard. One

example for this is Jeffrey C. Dixon (2010), who suggests that European identity might have a positive

effect on support for enlargement. Nevertheless two different lines of argumentation will form the

focus of this study. Firstly it is argued that identifying with Europe means being open to

cosmopolitanism and upholding European values. This in turn leads to being more supportive of

European integration and consequently also support further enlargement (cf. Dixon, 2010, p. 132).

Building on the Social Identity Theory (SIT), a second line of argumentation points in the opposite

direction, namely that European identity favors an in-group feeling and therefore fosters oppposition

towards the entrance of other countries. The Social Identity Theory, as developed by Henri Tajfel and

Turner (1986), theorizes that an individual identifies with the group he or she belongs to and therefore

creates an in-group feeling, which results in the exclusion of the other. Tyler M. Curley (2009) in

particular points out that European identity negatively effects support for Turkish accession. Based on

the SIT, the author constructs the theory that the stronger someone identifies himself with the

European Union, the more likely that person is to oppose Turkish accession.

The puzzle that evolves from these adverse views, namely whether European identity has a negative or

a positive influence on public opinion formation in regard to Turkish EU accession, will form the key

element of this paper. Therefore the following research question will be guiding the study:

‘Does individual identification with Europe have a positive or negative effect on the opinion formation of

EU citizens in regard to the potential EU- membership of Turkey?’

Due to the fact that SIT is playing an increasingly crucial role within the fields of political psychology and

even international relations, this study will focus mainly on the newer SIT approach when constructing

an applicable theory and will handle the cosmopolitan value-based theory as an alternative hypothesis.

Hence this paper seeks to expand the present knowledge surrounding public opinion towards Turkish

EU-membership by applying SIT. In order to contribute to the discussion of the underlying factors of

public opposition, this study advances the theory developed by Curley (2009). As opposed to his work

however, it does not lay the focus on the different national decision-makers, but will rather test Curley’s

hypothesis applied to the European public. To address this task, Eurobarometer data from 2008

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containing the level of individual identification with the European Union and support for an accession of

Turkey are analyzed. In order to increase the value of the study, data from all 27 member states (MS)

are examined using a multiple regression analysis.

2. Theory

As pointed out above, various explanations for factors determining the rather large opposition towards

Turkish EU-membership have been offered within the scientific community. The explanations range

from ‘hard’ rationalist’s to ‘soft’ constructivist’s accounts.

2.1. ‘Hard Factor’ Explanations

A considerable amount of scholars perceive utilitarian self-interest as a main factor influencing the

opinion towards EU enlargement. These studies of cost-benefit calculations of individuals or groups

have been a dominant part of the discussion (cf. for example Anderson & Reichert, 1996; Baldwin,

Francois, & Portes, 1997; Mahler, Taylor, & Wozniak, 2000). The concerned studies argue that

individuals are opposed to enlargement when they perceive it to negatively affect them personally

and/or the group they see themselves belonging to (cf. McLaren, 2007). Groups might be for example

the nation, the region or even the occupational group. As the internal market with its free movement of

goods, capital, services, and persons interlinks the economies of all member states, it is often suggested

that those with low-skilled jobs and low income levels are potentially hit the hardest by an enlargement

(cf. McLaren, 2007; Mahler et al., 2000). Scholars support this theory by arguing that low-skilled jobs are

more easily replaceable by cheaper migrating labor, or by companies moving to cheaper areas.

Additionally it is often argued that European institutions as the Common Agriculture Policy facilitate

such benefits on EU citizens, that these are unwilling to give up or share these benefits with citizens

from new member states. Therefore the hypothesis that low-skilled workers and farmers are generally

more opposed towards further EU enlargement plays an important role within the concerned literature.

As pointed out by Tyler M. Curley however this ‘rational choice theory’ does not fully account for the

explanation of support for EU enlargement. For if economic self-interest is the dominating factor, how

can we explain the larger opposition against Turkey’s membership as opposed to rather moderate

opposition towards the East enlargement in 2004 and 2007? This holds taking into account the

difficulties to argue that Turkey resembles a much greater economic threat now than the new member

states did some years ago (cf. for example Lejour & de Mooij, 2005).

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2.2. ‘Soft Factor’ Explanations

In the case of public opinion towards Turkey scholars have argued that in addition to economic self-

interest other factors play an important role too. The above discussed ‘hard factors’, as compared to

‘soft factors’, play a less vital role with regard to the discussion surrounding Turkey’s accession. De

Vreese et al. (2008) even claim that a shift has taken place, changing the focus of scholars from hard to

soft predictors “such as feelings of identity and attitudes towards immigrants” (de Vreese,

Boomgaarden, & Semetko, 2008, p. 512).

Marks and Hooghe (2003) differentiate between hard (economic) and soft (cultural) threats to the

nation-state in a similar way as between hard and soft factors in determining opposition towards Turkey

(cf. Kritzinger, 2003). Since a perceived or real threat to one’s economy or culture is always related to

one’s identification with a certain group, the role of identity also plays an important role in the

enlargement discourse within Europe. Therefore a number of studies dealing with the influence of the

people’s in-group feelings on the opposition against EU enlargement have been published (Dixon, 2010).

However only in few instances scholars studied the role of an overall European identity in the

opposition/support formation towards Turkey as a candidate state (cf. Curley, 2009; Dixon, 2010).

These studies about EU identity however, seem to branch off into two different directions. One way of

bringing European identity into the discussion on the opposition towards Turkey’s membership was

highlighted by Karp and Bowler (2006). They argued that a positive relationship exists between the

feeling of being European and supporting the expansion of the EU. Their study argues that a feeling of

European identity generally fosters the support for further European integration. The authors arrive at

this conclusion by assuming that if citizens feel more European, they are generally in favor of European

integration as such and consequently will be also more in favor of further enlargement. Hence a “kind of

pan-European nationalism, then, is likely to be associated with support for enlargement” (Karp &

Bowler, 2006, p. 371). In addition J.C. Dixon (2010, p. 132) refers to Karp and Bowler (2006) when stating

that “European identity indicates openness to cosmopolitanism and leads to greater support of the

European project”. Following this logic, a person identifying himself strongly with the European Union

would consequently be more in favor of enlarging the EU in order to deepen and diffuse the European

structures and value system.

Contrastingly, other scholars however have hypothesized that the role of European identity in light of

opinion formation might be of a completely different nature. As pointed out before the focus for this

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paper’s theory lies on the Social Identity Theory. This theoretical framework assumes that an individual

acquires multiple ‘social identities’ that are aligned with different social groups the individual perceives

himself belonging to. Meaning that membership in a group creates a certain in-group feeling (cf. Brown,

2000, p. 747). This feeling enhances a favoring behavior towards in-group members as compared to

outgroup individuals (i.e. in-group favoritism). Additionally the theory contends that members of a

group are more inclined to categorize individuals as outsiders than to include them into their own group

(i.e. the “over-exclusion effect”) (Curley, 2009, p. 650). Applying this to the EU enlargement by Turkey, it

can be argued, that the awareness of being a citizen of the European Union creates an in-group feeling.

According to some scholars, the feeling of belonging to one group leads to easily differentiating oneself

from ‘the other’ (cf. Curley, 2009). As defining the other is always an important part of defining oneself

(cf. Diez, 2004, p. 321), European citizens might theoretically define themselves vis-à-vis non-EU citizens,

i.e. Turks. This argument is supported by Thomas Diez who argues that since the 1990s “geographic and

cultural otherings” are once more increasing within Europe, meaning that differences as for example

religious affinity becomes again more important in identity construction. The Social Identity Theory is

further strengthened by Perreault and Bourhis (1999) who argue that the stronger individuals identify

themselves with their in-group, the more likely they will discriminate against individuals from an

‘outgroup’. Translated to the present case, this would mean that EU citizens that identify themselves

with Europe are more likely to discriminate in one way or the other towards Turkish citizens.

As mentioned in the introduction, Tyler M. Curley made use of SIT in order to show how, in the case of

Turkish accession, European identity will negatively affect the decision-makers’ support for Turkish

accession. He constructs the above mentioned theory that a stronger European identity triggers a

stronger in-group feeling within the European Union. In line with this argument the hypothesis that “the

stronger a decision-maker identifies with Europe, the stricter he/she will be when deciding which country

should be allowed entrance into the EU”, is derived by the author (Curley, 2009, p. 650).

Curley (2009, p.650) himself acknowledges, that the study only suffices to “provide a preliminary

examination of the theory”. He only studies very broadly the decision-makers’ identification with Europe

and attitudes towards Turkey’s accession, and furthermore limits his study to three countries1. The

present paper will employ the initial theoretical approach by Curley in order to construct a broader

theory, extending to the EU public opinion in the case of Turkish EU-accession. Thereby this paper

1 The countries under study are the United Kingdom, Germany, and France (cf. Curley, 2009)

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contributes to understanding public opinion formation and tests Curley’s hypotheses surrounding

European identity using new empirical data.

There are various ways to conceptualize European identity (e.g., see Maier & Rittberger, 2008; Bruter,

2003; Dixon, 2010). One important distinction between the conceptualizations stems from the

distinction between cultural and civic factors of identity. The cultural European identity is defined by the

belief that Europeans belong together due to shared values and cultural traits. The civic European

identity on the other hand has the supposition that identity forms through the political unity of a

community. Hence when Europeans “feel that they are citizens of a European political system, whose

rules, laws, and rights have an influence on their daily life”, a civic identity can be established (Bruter,

2003, p. 1155). In the realm of this paper the concept takes into account if a personal feeling of

belonging to Europe is existent, the feeling about belonging to Europe, and the personal importance of

being European2. Including these three sides of self- assessment contributes to the here used concept of

European identity, as it grasp not only the ‘feeling of belonging’ but also the own opinion about this fact.

This means that if people do feel that they belong to Europe – e.g. because their nation is a member of

the European Union – but have no personal importance attached to this, the concept used here will

measure this particular ambivalence.

Additionally also other more elementary factors as the perception of what the ultimate goal of the EU

should be might have an influence on the attitude towards enlarging the EU. In what way the final goal

of the European project is seen – a simple free trade area or a full political union – might for example be

an important factor for support. If the prevailing opinion is that the European Union should merely be a

free trade area and should be limited in its sovereignty and jurisdiction, it is very likely that enlargement

as such is perceived more positive. This is due to the fact, that the mere formation of a bigger single

market is likely to be more profitable. The citizens of the United Kingdom serve as an example for this

possibility as well, as the UK has always been one of the strongest opponents of ‘deeper’ European

integration (cf. Medrano, 2003). It is widely known, that in the UK the EU is valued more in terms of the

single market than for social or political unity. Therefore enlarging to for example either Norway or

Turkey wouldn’t make such a difference in terms of their culture, but in terms of their profitability for

the overall Union. However if the EU is seen more as an institution representing values and norms, being

steadily on the move to increase its sovereignty, enlarging to a new country might prove to be more

2 As it would exceed the scope of this study, the reasons for this ‘feeling of belonging to Europe’ – may it be for

civic or cultural reasons – are not considered here.

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difficult. When culture and other social aspects become more important within the debate, the

discussion about a widening gets more diversified. Once the focus lies on a deeper integration, a further

widening of the Union might impede the ‘deepening’. Furthermore in this discussion values and norms

would play a far more important role and therefore it would be distinguished differently between the

countries to which enlargement would be possible. In a debate dominated by these factors, the

question of whether Norway or Turkey would be more suitable as a member would be much clearer

sided to Norway. Nonetheless, the debate surrounding the particular accession of Turkey is paved with

concerns related to societal and cultural issues. Therefore it is crucial to similarly take into account that

nationality might be an interfering variable and consequently check for any patterns which might be

observable within the analysis of the impact of the different nationalities. Including the possible impact

of different national identities of all 27 EU MSs will enhance the explanatory power of this study.

2.3. Hypotheses

Both the hard and soft explanations of public opinion formation contain critical tools to understand why

so many oppose Turkish membership. However as many studies have been dealing with the cost-benefit

analyses and the consequential public opinion formation, this paper focuses on the rather understudied

section, namely the role of European identity in public opinion formation. In order to test the

applicability of the theories on the present case, the following hypotheses are constructed.

Taking into account the above mentioned theories, the SIT hypothesis by Curley (2009) is adjusted in

order to be applied to the theoretical framework concerning the public opinion of EU citizens.

H1: ‘The stronger an individual identifies with Europe, the stronger he/she is opposed to Turkey’s EU-

membership.’

However as established above, the role of identity within public opinion formation is contested.

Therefore also an alternative hypothesis is included in order to test whether the theory by Karp and

Bowler (2006) is more significant in explaining support and opposition towards Turkey’s membership.

H1 alt.: ‘The stronger an individual identifies with Europe, the stronger he/she will support Turkey’s EU-

membership.’

Theorized by McLaren (2007) is the relationship between a general feeling towards immigration and the

opinion towards Turkish membership. As there are a great number of Turkish migrants in different

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current member states of the EU, a general negative feeling towards migration might influence the

opinion towards a Turkish membership negatively. This approach is developed here into the following

hypothesis.

H2: ‘The more negative a person perceives immigration in general, the more he/she is opposed to

Turkey’s EU-membership.’

As mentioned above scholars as McLaren (2007) and Mahler et al. (2000) have argued that the

socioeconomic position is likely to affect the attitude towards enlargement because of the fear to loose

economically in the altered situation.

H3: ‘The lower a person’s socioeconomic position, the more likely he/she is opposed to Turkey’s EU-

membership.’

As touched upon above, the nationality might have different influences on the individual opinion as well.

Therefore dummy variables of all MSs are introduced in order to check for significant outliers among the

member states of the European Union.

3. Methodology

3.1. Research design

As the research question of the present study hints at the examination of a large population – i.e. all

European citizens living within the borders of the EU – a secondary analysis of an EU-wide public opinion

survey is the most appropriate research design. The standardized questionnaire employed in the used

survey strengthened the choice of this measurement, as it helps to make “refined descriptive

assertions” about the population and therefore strengthens the external validity of the study (Babbie,

2007, p. 276). Reliability and also external validity are ensured through the random selection and the

great sample size. Naturally however the standardized questions also form a validity weakness of the

study itself. This is due to the fact that a survey can never entirely grasp the different layers of public

opinion and mostly simply denotes a common denominator in its answers and thereby often seems

superficial (cf. Babbie, 2007, p. 276). Furthermore using an earlier conducted survey for a secondary

analysis depicts a possible threat to construct validity. In order to counteract this, a precise and

throrough conceptualization and operationalization of the variables is crucial.

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In order to test the constructed hypotheses, the Eurobarometer (EB) survey 69.2 from spring 2008 is

used. This particular survey is chosen, as it contains data referring to a wide range of questions that are

needed to answer the central question of this paper. EB is a frequently used dataset by scholars, as it

gives coherent and European-wide answers pointing at the mood and opinion of European citizens (cf.

for example Karp & Bowler, 2006 or Timus, 2006). Drawing for every EB new and independent samples,

the survey uses a “multi-stage, random (probability)” sampling design (Moschner, 2010). In this

particular EB survey 30,170 people were interviewed in all EU member states and some neighboring

nations3 (cf. Moschner, 2010). However the data set is filtered as to exclude the respondents from the

non-EU 27 countries. Thereby the number of respondents is decreased to 26,661; nevertheless the

sample is still representative with around 1,000 respondents per EU member state.

In order to grasp the whole of the EU public to the greatest extent possible, this paper expands the

framework developed by Curley to an empirical data analysis of the opinion of European citizens from all

27 member states. This renders a more valid generalization possible and gives a good overview on the

entire EU public opinion. It is acknowledged that an analysis of data over time would significantly

strengthen the results of the study, but unfortunately these data are only available in this form for the

year 2008. Nevertheless this paper gives a good insight on the applicability of the theories described

above.

To analyze the data, an ordinal regression analysis is employed in this study. Although the form of

variables might suggest using a logistic regression, the complexity of such an inquiry would exceed the

scope of this study. Additionally it is generally accepted that the logistic regression analysis is much

more difficult to interpret and inherits more stumbling blocks in general. Due to these reasons an

ordinal regression is chosen, acknowledging however, that this necessitates great caution when

interpreting the findings.

3 Non-EU member state that took part in the survey are: Turkey, Croatia, Cyprus (TCC), Macedonia

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3.2. Operationalization

In order to measure the dependent variable of the study, ‘attitude towards Turkey’s EU membership’,

question QA45 will be used:

“Once Turkey complies with all the conditions set by the European Union, would you be strongly in

favor, fairly in favor, fairly opposed or strongly opposed to the accession of Turkey to the European

Union? “

This question incorporates the assumption that Turkey will comply with the acquis communitaire and

therefore precisely points at the personal and more or less emotionally determined opinion towards

Turkish membership as such. To be able to display the relationship between the variables more

coherently, the answers are recoded the other way around, hence ranging from one (strongly opposed)

to four (strongly in favor). Furthermore to fit this data to the overall statistical analysis, a scale is

constructed ranging from zero to ten. Hence on the ‘Support for Turkey’ scale zero denotes strong

opposition towards a Turkish EU membership and ten denotes strong support.

The key independent variable, namely the ‘level of individual identification with Europe’ is less

straightforward to measure. As identity as such is already a very complex and hardly measurable

concept, European identity with its multifaceted character throughout the diversity of interpretations

makes it even more difficult. The variable constructed here measures different aspects of individual self-

assessment and thereby gives a clearer picture of a persons’ identification with Europe. This study uses a

scale created from three different EB questions in order to grasp the concept as thoroughly as possible

(QB1.1, QB2, QB4):

1. “Thinking about this, to what extent do you personally feel you are European?” (Answers: ‘to a great

extend’, ‘somewhat’, ‘not really’, and ‘not at all’) (v456)

2. “How do you feel about being European - on a scale from ‘1’ to ‘10’ - where ‘1’ means you feel not

content at all to be European and ‘10’ means you feel very content to be European?” (v460)

3. “Some things people consider to be extremely important to them, other things less so. Thinking now

about the fact you are European, how important is being European to you personally?” (Answers:

‘Being European matters a lot to you’, ‘Being European matters somewhat to you’, ‘Being European

does not matter much to you’, ‘Being European does not matter at all to you’) (v468) (European

Commission , 2008, pp. 43-46)

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All three items point into the direction of how far individuals identify with the European Union and

Europe in general. Combining the answers to all three questions provides the study with a measurable

variable of the level of individual identification with Europe. The internal consistency of the scale is

ensured by the high correlation between different items (cf. DeVellis, 2003, p. 28). The calculated

Cronbach’s coefficient alpha of 0,816 is high enough to underline this assertion.

In order to construct a variable showing the personal identification with Europe, a scale is constructed

adding up the separate answer scores. However to be able to do this, the questions have to be made

comparable scoring from one to four, in which four denotes the highest contribution to European

identity variable. Therefore the answers of v456 and v468 are recoded into new variables (v456new and

v468new) in which four denotes the answer possibility that contributes the most (‘to a great extend’ &

‘matters a lot’); hence the variables are reverse coded. The answers to v460 are furthermore recoded in

order to achieve a scale ranging as well from one to four (v460new); as opposed to one to ten. The

actual independent variable (v900; European identity), which will be used in the analysis, is constructed

applying an applicable formula4 in order range from 0 (not identifying with Europe at all) to 10

(identifying solely with Europe).

To be able to warrant the study against the interference of other explanatory variables, a number of

control variables are introduced in the following.

Hypothesis H2 incorporates the concept of ‘feeling towards immigration’. This variable is difficult to

measure, as no EB question points directly to this concept. Therefore an index is constructed, using two

EB questions5. The first question asks for the two most important issues in the respondents’ country and

offers immigration as a possible answer. The answers hereto are coded with 0 (immigration not

mentioned as important issue) or 4 (mentioned as important issue). The second question asks the

respondents if they agree with the statement that “immigrants contribute a lot to (OUR COUNTRY)”

(European Commission , 2008, p. 57). The answers to this are coded ranging from 1 (totally agree) to 4

(totally disagree). In order to construct the index measuring the respondents’ opinion on immigration to

4 The formula used is the following:

( )

5 QA6a: What do you think are the two most important issues facing (OUR COUNTRY) at the moment?

QD1a: For each of the following propositions, tell me if you totally agree, tend to agree, tend to disagree, totally disagree or don’t know? – 4. Immigrants contribute a lot to (OUR COUNTRY). (European Commission , 2008, p. 57)

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their country in general, the answers to both questions are summed up and recoded. To bring this

variable in line with the others, the new variable is transformed to range from 0 to 106.

As mentioned before scholars as McLaren (2007) and Mahler et al. (2000) have argued that especially

blue-collar workers and unemployed are likely to oppose EU enlargement due to self-interest based fear

of getting ousted by cheaper labor. This is tested in hypothesis H3 using the concept of socioeconomic

status. The current occupation of the respondents conceptualizes this variable. The questions “what is

your current occupation” (European Commission , 2008, p. 77) is used to operationalize this

independent variable. Having found a differently constructed scale (including the length of the

respondents’ education) to be not adequate enough, another form of variable is chosen. It appears

more suitable to use the occupation variable as a nominal variable in order to see the differences

between white-collar, blue-collar workers, unemployed and retired. Therefore the answers are coded

into unemployed (0), blue-collar workers (1), white-collar workers (2), and retired (3). While

constructing the dummy variables using this recoded variable (v771new) the white-collar workers

function as the baseline as it is expected that all other attributes are scoring lower on the Support for

Turkey scale in general7.

Lastly as laid out above the findings are controlled for the respondents’ origin. As this paper studies the

public opinion of EU citizens only, the data is filtered in such a way, that only respondents from the 27

EU member states are taken into account in the analysis. Using the available data stating the

nationalities of the respondents however can furthermore help increasing the value of this study. By

taking into account differences in the findings regarding all member states of the European Union, the

study also tries to identify patterns of nationality influence as laid out above. For this purpose the

answers to question Q1, asking for the respondents’ nationality, are recoded into 28 dummy variables8.

Italy functions here as a baseline as it lies almost at the exact mean of 4.70 of the Support for Turkey

variable (cf. Table 5). Hence the difference between the other countries and Italy will display the impact

of the EU member states on the models constructed within this paper.

6 The formula applied here is the following:

( )

7 List of dummy variables: vD1 (unemployed); vD2 (blue-collar worker); vD3 (retired)

8 The number of 28 originates from the fact that Northern Ireland and Eastern Germany were coded as single

nationalities by the researchers conducting the survey. Subtracting the baseline variable, one ends up with 28 dummy variables.

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One issue regarding the respondents’ origin however still persists. If the subjects are of Turkish origin,

this might skew the overall findings of the study, as they are most likely more positive towards a Turkish

accession. Unfortunately the Eurobarometer 69.2 only asks the respondents for their actual nationality

and not for their descent. This might pose a threat to the study’s reliability as respondents of Turkish

origin cannot be filtered out and although they might feel European and identify themselves with the

EU, they are more likely to also sympathize with Turkey. Hereby the issue of multiple identities comes

into play, where people of Turkish origin might feel European and Turkish at the same time. However it

is expected that the number of respondents with a migration background from Turkey is low enough to

neglect this problem.

Having a first glance at the descriptive statistics in Table 1 (see Appendix), shows that 23,922 people

answered the question whether they would support a Turkish accession to the EU when all conditions

are complied with. The responses are quite evenly distributed over being supportive and unsupportive

of a possible admittance. Neglecting the missing data (accounts for merely 10%) for the independent

variable, 48.7% of the respondents are fairly or strongly opposed to a Turkish membership. A mean of

4.70 is calculated, which shows on a scale from zero to ten (where ten denotes ‘strongly in favor’) that

this particular question does not reflect the public opinion as negatively as expected (cf. Table 5).

Another question of the Eurobarometer 69.2 however shows a different pattern of answers. It simply

asks: “For each of the following countries and territories, would you be in favour or against it becoming

part of the European Union in the future?” (European Commission, 2008, p. 35) The responses to this

question resemble better the expected negative opinion; namely 62.6% checked ‘against’ a membership

of Turkey. Nevertheless in order to perform a regression analysis, whether the expected distribution of

answers is matched is not decisive. Therefore this paper proceeds using the earlier constructed variable

‘Support for Turkey’.

However Table 1 furthermore shows that the mean of the key independent variable, i.e. European

Identity, lies at 6.32. This illustrates that most of the EU citizens that participated in the survey identify

themselves quite substantially with Europe. The mean of Immigration Control amounts to 3.22,

suggesting that more respondents have a rather positive feeling towards immigration as such.

Page | 17

4. Analysis

Figure 2 gives a first hint on the initial relationship of hypothesis H1. The scatterplot (using the mean

values of the dependent variable for the various values of the independent variable) shows a positive

linear relationship between supporting Turkish membership and identifying with Europe. The direction

of the relationship is positive, which gives a first reason to believe that H1 is after all hypothesizing the

wrong correlation, thereby strengthening H1alt. However this initial correlation is not enough to prove

that European identity indeed influences the opinion for Turkey’s EU membership positively. Therefore

an ordinal regression analysis is applied in the following. In order to also statistically control for other

explanatory factors, as laid out in the theory section of this paper, additional variables – i.e. the feeling

towards immigration, the kind of occupation and the nationality – are included in the following

regression analyses. This gives assistance to understanding the influence of each of these variables and

how they explain the support for the accession of Turkey. Four regression models are included in the

analysis introducing one variable at a time.

Page | 18

The first model includes the key independent variable ‘European Identity’ and the dependent variable

‘Support for Turkey’. As can be drawn from Table 2, the R² value for this model is 0.039, meaning that

European identity explains 3.9% of the overall level of support for a Turkish membership.

Table 2: Model Summary with dependent variable ‘Support for Turkey’

Model R R² R² Change Sig. F Change Durbin-Watson

1 0.196 0.039 0.039 0.000

1.732

2 0.283 0.080 0.042 0.000

3 0.287 0.082 0.002 0.000

4 0.376 0.141 0.059 0.000

Table 3 illustrates that the b-value of the variable European Identity is 0.271. This means that when a

person’s identification with Europe on the here employed scale increases by one unit, the respondent

shifts 0.271 units up on the Support for Turkey scale. This shows that the relationship between

European Identity and Support for Turkey is, as already suggested above, positive. This finding

significantly strengthens the claim that hypothesis H1alt is actually containing the correct relationship.

These findings are significant at the 0.001 level, as also shown in Table 3. Having established that the

main interaction between the key independent variable and dependent variable of the study is positive,

the analysis now turns to assessing the impact of the proposed control variables.

Table 3: Coefficients with dependent variable ‘Support for Turkey’ - 1

Model Unstandardized Coefficients Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 2.976 0.062 47.962 0.000

European

Identity

0.271 0.009 0.196 29.529 0.000

2 (Constant) 4.288 0.074 58.138 0.000

European

Identity

0.233 0.009 0.161 24.447 0.000

Immigration

Control

-0.312 0.010 -0.207 -31.310 0.000

Page | 19

Hypothesis H2 suggests that the more negative a person feels towards immigration, the more he/she is

against Turkey joining the EU. This approach is included in model two, hence extending model one with

the variable Immigration Control. Taking a look at Table 2 again shows that the R² value increases by

0.41, bringing it up to 8%. This indicates the explanatory power of the immigration variable within the

model as it nearly doubles the R² value of model one. Looking at the unstandardized coefficients, the b-

value reveals that the relationship is negative (-0.312) and the t-test value shows that it is highly

significant. This confirms the hypothesis that EU citizens are more opposed to Turkish accession when

they have a more negative attitude towards immigration in general. However this does not change the

impact of the key independent variable notably, as the b-value of European Identity decreases merely by

0.038 to 0.233.

In model three the constructed dummy variables of the respondents’ occupation are added. However

when viewing Table 2 we see that these dummy variables add only little explanatory power as compared

to the previous model. The R² value increases only by 0.02 to 8.2%, hence the kind of occupation does

not seem to explain the support for Turkey very well. Having a look at the coefficients again brings

unexpected findings to light. As Table 4 shows, the b-value of ‘Unemployed Dummy’ is 0.256 and the

one of ‘Bluecollar Dummy’ is 0.041. Remembering that white-collar workers functioned as a baseline

when constructing these dummies, these results mean that unemployed and blue-collar workers are

actually more inclined to be rather positive towards the admittance of Turkey to the EU than are white-

collar workers. However it has to be noted, that the ‘Bluecollar Dummy’ is not significant at the 0.1 level.

For ‘Retired Dummy’ the case is different. Here the b-value amounts to -0.177, meaning that only retired

people are more inclined to be more negative towards a possible Turkish accession than white-collar

workers. This finding is very odd, as it is mostly argued in the academia that blue-collar workers and

unemployed are more afraid of being negatively affected by an enlarging European Union. Getting back

to the b-values of the variables added in the previous models (i.e. European identity and Immigration

Control), shows that adding the occupation dummy variables had little or no effect on the relationship

between them and the dependent variable Support for Turkey. Hence for the key independent variable

this means that the impact of European identity on the opinion towards Turkey’s accession is more or

less the same over all kinds of occupations.

Page | 20

Table 4: Coefficients with dependent variable ‘Support for Turkey’ - 2

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

3

(Constant) 4.271 0.080 53.085 0.000

European

Identity

0.223 0.009 0.162 24.426 0.000

Immigration

Control

-0.311 0.010 -0.206 -31.112 0.000

Unemployed

Dummy

0.256 0.060 0.031 4.243 0.000

Bluecollar

Dummy

0.041 0.063 0.005 0.650 0.561

Retired Dummy -0.177 0.055 -0.024 -3.204 0.000

4 (Constant) 4.254 0.133 32.015 0.000

European

Identity

0.211 0.009 0.153 22.664 0.000

Immigration

Control

-0.300 0.010 -0.198 -29.575 0.000

Unemployed

Dummy

0.249 0.059 0.030 4.191 0.000

Bluecollar

Dummy

0.078 0.062 0.009 1.251 0.211

Retired Dummy -0.190 0.054 -0.026 -3.528 0.000

France Dummy -0.952 0.151 -0.057 -6.299 0.000

Belgium

Dummy

-0.080 0.149 -0.005 -0.538 0.591

Netherlands

Dummy

1.454 0.149 0.090 9.761 0.000

WGermany

Dummy

-1.166 0.150 -0.071 -7.769 0.000

Luxembourg

Dummy

-1.489 0.183 -0.064 -8.135 0.000

Denmark

Dummy

0.531 0.149 0.033 3.555 0.000

Page | 21

Ireland Dummy -0.361 0.164 -0.019 -2.208 0.27

Great Britain

Dummy

0.375 0.157 0.021 2.394 0.017

Northern

Ireland Dummy

0.582 0.228 0.018 2.547 0.011

Greece Dummy -0.194 0.147 -0.012 -1.318 0.187

Spain Dummy 0.670 0.160 0.036 4.187 0.000

Portugal

Dummy

0.527 0.159 0.029 3.317 0.001

EGermany

Dummy

-0.918 0.182 -0.040 -5.041 0.000

Finland Dummy -0.399 0.150 -0.025 -2.666 0.008

Sweden Dummy 1.130 0.151 0.069 7.495 0.000

Austria Dummy -2.140 0.154 -0.124 -13.923 0.000

Cyprus Dummy 0.164 0.180 0.007 0.907 0.364

Czech Republic

Dummy

-0.052 0.153 -0.003 -0.342 0.732

Estonia Dummy 0.426 0.155 0.024 2.742 0.006

Hungary

Dummy

0.856 0.156 0.049 5.501 0.000

Latvia Dummy 0.299 0.155 0.017 1.927 0.054

Lithuania

Dummy

0.145 0.157 0.008 0.927 0.354

Malta Dummy 0.254 0.204 0.009 1.246 0.213

Poland Dummy 0.802 0.162 0.042 4.954 0.000

Slovakia

Dummy

-0.498 0.151 -0.030 -3.307 0.001

Slovenia

Dummy

0.218 0.152 0.013 1.433 0.152

Bulgaria

Dummy

0.274 0.167 0.014 1.637 0.102

Romania

Dummy

1.173 0.167 0.059 7.041 0.000

Page | 22

Despite the fact that 28 new variables denoting the different nationalities in the EU are added at once in

model four, the change in the impact of the earlier added variables is almost non-existing. Starting with

R² again, it becomes obvious however that this model has the greatest explanatory power of all four

models discussed here. With 14.1% the R² value increased significantly by 0.059. Coming to the b-values

of this model, only the country dummies standing out will be mentioned in this analysis. Nevertheless

the effect on the earlier introduced variables should be noted. The b-value of European Identity

decreases in this model by 0.012 to 0.211 and Immigration Control decreases by almost the same (by

0.011) to -0.300. This shows that after allowing for the linear effects of the other variables in the model,

an increase of one unit on the European Identity scale is associated with an increase of 0.211 units on

the Support for Turkey scale and a decrease of 0.300 on the Immigration Control scale. This shows that

the European identity’s effect on Support for Turkey remains more or less the same over all country

samples. Employing the t-test shows that the contribution to the model by the immigration variable is

the highest (t = -29.575 with Sig. < 0.001), followed by European Identity (t = 22.664 with Sig. < 0.001).

Supporting the quality of the models are the confidence intervals. The confidence intervals of model

four show that with a 95% confidence, the true b-value for European Identity between 0.192 and 0.229

and for Immigration Control lies between -0.320 and -2.80. These quite narrow ranges let assume that

the model is well constructed and meaningful. Two of the three occupation dummies (retired and blue-

collar) actually increase when adding the effect of the nationalities. However shrinking in its b-value, the

unemployed dummy decreases merely by 0.007. Coming to the nationality dummies, six values are

striking and nine others are not significant at the 0.05 level9 (cf. Table 4). As can also be seen in Table 4

the mentioned six countries all differ considerably from the baseline, i.e. Italy’s value. The Netherlands,

Sweden and Romania have b-values that exceed 1.000. Contrasting West-Germany, Luxembourg and

Austria score below -1.000 at the unstandardized coefficients. Austria has to be noted as an extreme

outlier, as it shows a value of -2.140.

Table 5 depicts the distribution of all member states in two categories, namely those with higher values

and those with lower values as compared to the baseline Italy. This table shows that all in all 17

countries score higher and eleven countries score lower as compared to Italy. When dividing the

countries into old and new member states – i.e. countries that joined the Union before 2004 and

countries that joined later – a pattern of distribution can be made out. Ten out of 17 countries are new

member states that score higher on the b-value, this equivalents to 83% of all new MS. Conversely only

9 Non-significant findings correspond to following countries: Belgium, Greece, Cyprus, Czech Republic, Lativa,

Lithuania, Malta, Slovenia and Bulgaria.

Page | 23

two out of eleven are new MS in the group of countries that score lower as compared to Italy, or the

median respectively. This number corresponds to merely 17% of all new member states. This means that

considerably more new MS are rather in favor than against a potential membership of Turkey.

Table 5: Countries’ b-values with Italy as baseline

Higher values Lower values

The

Netherlands

1.454 Austria -2.140

Romania 1.173 Luxembourg -1.489

Sweden 1.130 West Germany -1.166

Hungary 0.856 France -0.952

Poland 0.802 Slovakia -0.498

Spain 0.670 Finland -0.399

Northern

Ireland

0.582 Ireland -0.361

Denmark 0.531 East Germany -0.198

Portugal 0.527 Greece -0.194

Estonia 0.426 Belgium -0.080

Great Britain 0.375 Czech Republic -0.052

Latvia 0.299

Bulgaria 0.274

Malta 0.254

Slovenia 0.218

Cyprus 0.164

Lithuania 0.145

Total: 17 countries 11 countries

Including 83% of all new MS

Including 17% of all new MS

Having looked at the individual scores of all models, the study will now turn to checking several

assumptions in order to create certainty about the quality of this analysis.

Overall the model summary of Table 2 shows that all changes are significant at the 0.001 level.

Furthermore the reader can see that the Durbin-Watson score is 1.732. Following the argumentation of

Andy Field (2009), this score is close enough to two in order to conclude that the assumption of

independent errors is tenable.

Page | 24

In order to check for the preclusion of multicollinearity, the average of the VIF values is calculated to be

1.81310. In order to assure the independence of the predictors, the eigenvalues and variance proportions

are additionally scanned by hand. As no high correlation is found, multicollinearity can be precluded.

All in all it has been shown, that European identity does have a significant effect on the opinion of

Europeans in regard to the accession of Turkey. Furthermore this relationship has been shown to be

positive, thereby confirming H1alt. However it also has to be noted that although European identity is a

significant predictor of the independent variable, the feeling towards immigration seems to have an

even greater impact on the Support for Turkey. Furthermore it was shown, that the kind of occupation

of the respondents has had the least impact on the dependent variable. Additionally the analysis of all

28 nationality dummies revealed that a few member states have a quite extreme view on Turkey’s

admittance and that the new MS are mostly more in favor of Turkey joining the EU.

5. Discussion and Conclusion

By determining the actual relationship between the individual identification with Europe and the

opinion towards a potential EU membership of Turkey, the paper at hand presented different views on

how factors might influence this opinion of European citizens. Next to predictors from the identity side

also factors determined by utilitarian self-interests were considered within the realm of this paper. Two

theories regarding the identity-related factors were contrasted in order to understand the impact of

European identity on the public opinion formation towards a Turkish accession to the EU. On the one

hand the widespread theory, that identifying with Europe incorporates being especially cosmopolitan

and consequently being more open to new members to spread the values and norms of Europe was

delineated. On the other hand the rather recent theory by Tyler M. Curley (2009), taking a somewhat

psychological approach to the issue, was applied.

By conducting a regression analysis using data from the Eurobarometer 69.2 from 2008, this study has

produced a couple of striking outcomes. The main finding of this paper is necessarily the conclusion that

the data does not support hypothesis H1. The positive significant relationship between a European

identity and the opinion towards a Turkish accession rather supports the alternative hypothesis H1alt.

This means that the more people feel European, the more they are inclined to support enlarging the

10

The average of the VIF scores was calculated as follows: ̅̅ ̅̅ ̅ ∑

See Table 6 in appendix for a list of all VIF scores.

Page | 25

Union to another member, namely Turkey. Therefore the more widespread theory has been

strengthened in the present empirical study, refuting the applicability of SIT on the studied case. This

finding holds over all four models analyzed, meaning that European identity has a general impact over

all kinds of occupations and all member states.

In terms of the Social Identity Theory, this finding hints at the conclusion that within the group of

European Union citizens a general in-group feeling is not as widespread as in other groups researched by

different social scientists. This might be explained by the assumption that the European identity is not as

strongly developed as might be necessary to create an in-group feeling for the citizens. It seems as the

European Union if it all forms a ‘group’ for people that hold in high esteem a certain degree of

cosmopolitanism, transcending local and national borders. That people identifying with Europe in this

specific way will strongly oppose enlargement to Turkey would constitute an obvious paradox. It

remains to be seen however, in what way the European Union as a pool of identity will develop in the

future. If the process will proceed at the pace it has taken over the last half a century, it might be

possible that soon also European identity lets people distinguish more carefully between them and

others. Coming back to the breakdown of identity formation by Bruter (2003) into civic and cultural

factors, it becomes clear that the European Union is on a clear path to establish a stronger European

identity. Examples for this endeavor are plentiful, ranging from cultural factors as for example EU

projects like the European Capital of Culture, to civic factors as the introduction of a European Union

citizenship. Hence it might be interesting for future research to keep an eye on the development of

European identity and the possible effects of such.

Another important finding of this study is the great impact of the feeling towards immigration on the

opinion on Turkey as a candidate country, supporting Hypothesis H2. The analysis showed that this

factor is even the strongest in predicting the outcome. As this factor amounts to only a rather small part

of the literature, this strong outcome is rather striking. Nonetheless it seems as a very logical

consequence, that people who perceive immigration negatively are also negatively tuned in the

question of Turkey joining the EU. This finding can most likely be explained by the often high number of

Turkish immigrants throughout Europe. The presence of these in might link the notion of general

immigration to Turkish people as such in many minds throughout Europe and thereby triggering such

important impact on the opinion.

Another striking finding regards the socioeconomic status and its impact on the opinion of the

Europeans. Throughout the literature the claim that the type of work influences the people’s opinion on

Page | 26

Turkey is widespread. However within this study the corresponding variables did not have a notable

impact as predictors. Furthermore only the group of retired people was more opposed to the idea of

Turkey joining the EU than white-collar workers were. These findings are so off the general opinion

within the academia, that more explicit empirical research focusing on this exact relationship is

necessary. Furthermore the suitability of the data may be doubted due to the fact that a secondary

analysis was conducted. It is also highly unlikely that the theory that unemployed and blue-collar

workers are more inclined to be opposed towards EU enlargement is not applicable in the case of

Turkey. Theoretically this would make little sense, as Turkey’s accession is often perceived as being the

gate opener for masses of cheap labor streaming onto European Union soil, taking most of the unskilled

jobs. Future research might pick up the potential problem of operationalization and try to come up with

more suitable data and measurement of the theory.

Coming to the impact of nationality a few things can be concluded from this analysis. Firstly it can be

noted that adding the nationality dummies to the regression model, increased its explanatory power

tremendously. The resulting findings however were not as straightforward. While a few outliers on both

ends were detected, not all of them are surprising. Striking was however the fact that being Dutch had

the greatest positive impact on the opinion towards Turkey’s accession. Although the Netherlands

always counts as a very liberal and pro-European country, a shift has taken place within the last years

favoring more right-wing movements. As the employed survey was conducted in 2008 this movement

might have been not as widespread as today. A different, clearer case applies for Sweden, which had a

similarly high score and is known for its pro-enlargement attitude. Romania, another high extreme

score, goes with its support for Turkey’s membership in line with most of the new member states that

joined the Union in the new millennium. The citizens of ten out of twelve new MS (83%) are more

inclined to be positive towards Turkey becoming a new MS. Despite the fact that this is the only pattern

that can be detected within the nationality analysis, this conjuncture is not very striking. It is often

theorized that the new MS are more in favor of further enlarging the Union as they themselves profit

much from being a member and know how important it can be for a country’s development to join.

The extreme scores on the other side of the scale, namely Austria, West Germany and Luxembourg, are

quite interesting. With -2.140 Austria diverts the most from the baseline Italy. That Austrians have been

a big criticizer of EU integration, especially since the EU sanctions of 2000, is a known fact throughout

Europe. That the citizens are against further enlargement is therefore consequential in this context.

West Germany’s reluctance to accept Turkey as a new member of the European Union can most likely

Page | 27

be explained through the found impact of immigration. As Germany inhabits with about 2 million Turks

the largest population of Turkish people outside Turkey and as integration problems are repeatedly

raised within the public, it is not surprising to find such big opposition. The slight difference between the

opposition in East and West Germany (difference of 0.248) can in this context be explained by the

significant difference in the percentage of foreigners in East and West Germany11. The extreme numbers

of Luxembourg seems to be striking however, as Luxembourg is perceived to be a more pro-European

country. Future research might try to shed light onto the underlying factors of this strong opinion.

All in all it has to be noted, that the here studied models explain about 14% of the independent variable.

Consequently it has to be assumed that there are a number of undiscovered factors explaining the other

86%. To identify these should be another goal of future research in order to get an even clearer picture

on the factors influencing the opinion of European citizens in regard to Turkey’s accession to the EU.

Nevertheless this paper presented an empirical insight on how the Social Identity Theory can or better

cannot be applied on the opinion formation of Europeans. For policy makers in Europe this finding can

be a relief, as it is now even clearer that a stronger European identity has the ability to enhance and

ease the integration process in terms of both, widening and deepening. Therefore, at least in this regard

no immediate decision has to be taken between a further enlargement and an internal integration of the

European Union. Almost certainly a way to enhance the legitimacy and the support for further enlarging

the European Union is to keep on working on and fostering a thorough European identity.

11

In 2006 the percentage of foreigners in West Germany amounted to 9.7%, whereas in East Germany only 2.4% were foreigners. (Bundeszentrale für politische Bildung , 2006)

Page | 28

Appendix Table 1: Overview of all variables, including operationalization and descriptive statistics

Variable Name Original Variables / EB Questions

Form of Variable

Range N Mean Std. Deviatio

n

Support for Turkey (v419end)

v419/ QA45 Scale 0- 10 23,922 4.6988 3.29466

European Identity (v900)

v456, v460, v468/ QB1.1, QB2, QB4

Scale 0- 10 25,288 6.2518 2.43152

Immigration Control (vC2end)

v119, v552/ QA6a, QD1a Index 0- 10 24,435 4.3767 2.48820

Unemployed Dummy (vD1)

v771/ QD15a Nominal Variable

0- 1 26,661 0.2118 0.40857

Bluecollar Dummy (vD2)

v771/ QD15a Nominal Variable

0- 1 26,661 0.1800 0.38420

Retired Dummy (vD3)

v771/ QD15a Nominal Variable

0- 1 26,661 0.2874 0.45255

France Dummy (vDFR)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0390 0.19362

Belgium Dummy (vDBE)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0376 0.19028

Netherlands Dummy (vDNL)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0390 0.19371

WGermany Dummy (vDDEw)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0358 0.19245

Luxembourg Dummy (vDLU)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0188 0.13579

Denmark Dummy (vDDK)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0377 0.19046

Ireland Dummy (vDIE)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0377 0.19037

Great Britain Dummy (vDUK)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0377 0.19055

Northern Ireland Dummy (vDNIR)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0113 0.10548

Greece Dummy (vDGR)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0375 0.19001

Spain Dummy (vDES)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0387 0.19299

Portugal Dummy (vDPT)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0375 0.19010

EGermany Dummy (vDDEe)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0190 0.13659

Finland Dummy (vDFI)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0377 0.19037

Sweden Dummy v6/ Q1 Nominal 0- 1 26,661 0.0378 0.19064

Page | 29

(vDSE) Variable Austria Dummy (vDAT)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0375 0.19001

Cyprus Dummy (vDCY)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0189 0.13619

Czech Republic Dummy (vDCZ)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0380 0.19128

Estonia Dummy (vDEE)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0377 0.19055

Hungary Dummy (vDHU)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0375 0.19001

Latvia Dummy (vDLV)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0378 0.19074

Lithuania Dummy (vDLT)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0383 0.19191

Malta Dummy (vDMT)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0188 0.13566

Poland Dummy (vDPL)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0375 0.19001

Slovakia Dummy (vDSK)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0407 0.19759

Slovenia Dummy (vDSI)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0376 0.19028

Bulgaria Dummy (vDBG)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0375 0.19001

Romania Dummy (vDRO)

v6/ Q1 Nominal Variable

0- 1 26,661 0.0382 0.19173

Valid N (listwise) 21714

Page | 30

Table 6: Coefficients with dependent variable ‘Support for Turkey’ - Complete

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

Coll.

Statistics

B Std. Error Beta VIF

1 (Constant) 2.976 0.062 47.962 0.000

European

Identity

0.271 0.009 0.196 29.529 0.000 1.000

2 (Constant) 4.288 0.074 58.138 0.000

European

Identity

0.233 0.009 0.161 24.447 0.000 1.030

Immigration

Control

-0.312 0.010 -0.207 -31.310 0.000 1.030

3 (Constant) 4.271 0.080 53.085 0.000

European

Identity

0.223 0.009 0.162 24.426 0.000 1.035

Immigration

Control

-0.311 0.010 -0.206 -31.112 0.000 1.033

Unemployed

Dummy

0.256 0.060 0.031 4.243 0.000 1.276

Bluecollar

Dummy

0.041 0.063 0.005 0.650 0.561 1.261

Retired

Dummy

-0.177 0.055 -0.024 -3.204 0.000 1.321

4 (Constant) 4.254 0.133 32.015 0.000

European

Identity

0.211 0.009 0.153 22.664 0.000 1.148

Immigration

Control

-0.300 0.010 -0.198 -29.575 0.000 1.135

Unemployed

Dummy

0.249 0.059 0.030 4.191 0.000 1.315

Bluecollar

Dummy

0.078 0.062 0.009 1.251 0.211 1.300

Retired

Dummy

-0.190 0.054 -0.026 -3.528 0.000 1.348

Page | 31

France

Dummy

-0.952 0.151 -0.057 -6.299 0.000 2.081

Belgium

Dummy

-0.080 0.149 -0.005 -0.538 0.591 2.158

Netherlands

Dummy

1.454 0.149 0.090 9.761 0.000 2.159

WGermany

Dummy

-1.166 0.150 -0.071 -7.769 0.000 2.113

Luxembourg

Dummy

-1.489 0.183 -0.064 -8.135 0.000 1.554

Denmark

Dummy

0.531 0.149 0.033 3.555 0.000 2.166

Ireland

Dummy

-0.361 0.164 -0.019 -2.208 0.27 1.793

Great Britain

Dummy

0.375 0.157 0.021 2.394 0.017 1.985

Northern

Ireland

Dummy

0.582 0.228 0.018 2.547 0.011 1.304

Greece

Dummy

-0.194 0.147 -0.012 -1.318 0.187 2.194

Spain

Dummy

0.670 0.160 0.036 4.187 0.000 1.868

Portugal

Dummy

0.527 0.159 0.029 3.317 0.001 1.897

EGermany

Dummy

-0.918 0.182 -0.040 -5.041 0.000 1.557

Finland

Dummy

-0.399 0.150 -0.025 -2.666 0.008 2.162

Sweden

Dummy

1.130 0.151 0.069 7.495 0.000 2.139

Austria

Dummy

-2.140 0.154 -0.124 -13.923 0.000 2.003

Cyprus

Dummy

0.164 0.180 0.007 0.907 0.364 1.569

Page | 32

Czech

Republic

Dummy

-0.052 0.153 -0.003 -0.342 0.732 2.052

Estonia

Dummy

0.426 0.155 0.024 2.742 0.006 1.995

Hungary

Dummy

0.856 0.156 0.049 5.501 0.000 1.988

Latvia

Dummy

0.299 0.155 0.017 1.927 0.054 1.965

Lithuania

Dummy

0.145 0.157 0.008 0.927 0.354 1.921

Malta

Dummy

0.254 0.204 0.009 1.246 0.213 1.442

Poland

Dummy

0.802 0.162 0.042 4.954 0.000 1.839

Slovakia

Dummy

-0.498 0.151 -0.030 -3.307 0.001 2.103

Slovenia

Dummy

0.218 0.152 0.013 1.433 0.152 2.092

Bulgaria

Dummy

0.274 0.167 0.014 1.637 0.102 1.728

Romania

Dummy

1.173 0.167 0.059 7.041 0.000 1.765

Page | 33

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